********************************************************************************
* RDPOW: power calculation for Regression Discontinuity Designs
* Authors: Matias Cattaneo, Rocío Titiunik, Gonzalo Vazquez-Bare
********************************************************************************
*!version 2.1 20-Jun-2022

version 13

capture program drop rdpow
program define rdpow, rclass

	syntax [anything] [if] [in] [, c(real 0) tau(numlist max=1) alpha(real .05) NSamples(string) sampsi(string) samph(string) all ///
											  bias(string) VARiance(string) ///
  											  plot graph_range(string) graph_step(numlist max=1) graph_options(string) ///
											  covs(string) covs_drop(string) deriv(real 0) p(real 1) q(numlist max=1) h(string) b(string) rho(real 0) ///
											  kernel(string) bwselect(string) vce(string) weights(string) ///
											  scalepar(real 1) scaleregul(real 1) fuzzy(string) level(real 95) ///
											  masspoints(string) bwcheck(real 0) bwrestrict(string) stdvars]


	****************************************************************************
	** Options, default values and error checking
	
	marksample touse, novarlist

	if "`anything'" != ""{
		local w: word count `anything'
		if `w'!=2{
			di as error "too few variables specified"
			exit 102
		}
		else {
			tokenize `anything'
			local y `1' 
			local x `2'
		}
	}
	
	local nodata = 0
	if "`nsamples'" != ""{
		if "`anything'" != "" {
			di as result "nsamples is ignored when varlist specified"
		}
		else {
			if "`bias'" != "" & "`variance'" != "" & "`samph'" != "" & "`sampsi'" != "" & "`tau'" != ""{
				local nodata = 1
			}
			else {
				di as error "not enough information specified to calculate power without data"
				exit 102
			}
			tokenize `nsamples'
			local w: word count `nsamples'
			if `w'==4{
				local nminus = `1'
				local n_hnew_l = `2'
				local nplus = `3'
				local n_hnew_r = `4'
			}
			else {
				di as error "insufficient arguments in nsamples"
				exit 198
			}
			capture confirm integer number `nminus'
			if _rc>0{
				di as error "sample sizes in nsamples have to be integers"
				exit 198
			}
			capture confirm integer number `n_hnew_l'
			if _rc>0{
				di as error "sample sizes in nsamples have to be integers"
				exit 198
			}
			capture confirm integer number `nplus'
			if _rc>0{
				di as error "sample sizes in nsamples have to be integers"
				exit 198
			}
			capture confirm integer number `n_hnew_r'
			if _rc>0{
				di as error "sample sizes in nsamples have to be integers"
				exit 198
			}
			
			if `nplus'<=0 | `n_hnew_l'<=0 | `nminus'<=0 | `n_hnew_r'<=0 {
				di as error "sample sizes in nsamples have to be >0"
				exit 198
			}
		}
	}
	

	if "`sampsi'" != ""{
		tokenize `sampsi'
		local w: word count `sampsi'
		if `w'==1{
			local ntilde_l = `1'
			local ntilde_r = `1'
		}
		if `w'==2{
			local ntilde_l = `1'
			local ntilde_r = `2'
		}
		if `w'>=3{
			di as error "sampsi incorrectly specified"
			exit 125
		}
		
		capture confirm integer number `ntilde_l'
		if _rc>0{
			di as error "sample sizes in sampsi have to be integers"
			exit 198
		}
		capture confirm integer number `ntilde_r'
		if _rc>0{
			di as error "sample sizes in sampsi have to be integers"
			exit 198
		}
		
		if `ntilde_l'<=0 | `ntilde_r'<=0{
			di as error "sample sizes in sampsi have to be >0"
			exit 198
		}
	}
	
	if "`samph'" != "" {
		tokenize `samph'
		local w: word count `samph'
		if `w'==1{
			local hnew_l = `1'
			local hnew_r = `1'
		}
		if `w'==2{
			local hnew_l = `1'
			local hnew_r = `2'
		}
		if `w'>=3{
			di as error "samph option incorrectly specified"
			exit 125
		}
	}
	
	if "`bias'" != ""{
		local bias_cond = 1
		tokenize `bias'
		local w: word count `bias'
		if `w'==1{
			di as error "need to specify both Bl and Br"
			exit 125
		}
		if `w'==2{
			local bias_l = `1'
			local bias_r = `2'
		}
		if `w'>=3{
			di as error "bias incorrectly specified"
			exit 125
		}
	}
	
	if "`variance'" != ""{
		tokenize `variance'
		local w: word count `variance'
		if `w'==1{
			di as error "need to specify both Vl and Vr"
			exit 125
		}
		if `w'==2{
			local Vl_rb = `1'
			local Vr_rb = `2'
		}
		if `w'>=3{
			di as error "variance incorrectly specified"
			exit 125
		}
		if `Vl_rb'<=0 | `Vr_rb'<=0{
			di as error "variances have to be >0"
			exit 198
		}
	}
	
	if "`covs'" != ""{
		local covs_opt "covs(`covs')"
		local ncovs: word count `covs'
	}
	
	if "`q'"==""{
		local q = `p'+1
	}
	
	if "`h'" != ""{
		local h_opt "h(`h')"
	}
	
	if "`b'" != ""{
		local b_opt "b(`b')"
	}
	
	if "`kernel'" != ""{
		local kernel_opt "kernel(`kernel')"
	}
	
	if "`bwselect'" != ""{
		local bwselect_opt "bwselect(`bwselect')"
	}
	
	if "`vce'" != ""{
		local vce_opt "vce(`vce')"
		local vce1 "`vce'"
		tokenize `vce1'
		local clust_opt `1'
		local clustvar `2'
	}
	
	if "`fuzzy'" != ""{
		local fuzzy_opt "fuzzy(`fuzzy')"
	}
	
	if "`bias'"!="" & "`variance'"!="" & "`samph'"==""{
		di as error "need to specify bandwidth in samph()"
		exit 198
	}
	
	if "`bias'"!="" & "`variance'"!="" & "`sampsi'"==""{
		di as error "need to specify sample sizes in sampsi()"
		exit 198
	}
	
	if "`bias'"!="" & "`variance'"!="" & "`all'" != ""{
		di as error "cannot set both bias and variance when all is specified"
		exit 198
	}
	
	if "`covs_drop'" != ""{
		local covs_drop_opt "covs_drop(`covs_drop')"
	}
	
	if "`masspoints'" != ""{
		local masspoints_opt "masspoints(`masspoints')"
	}
	
	if "`bwcheck'" != ""{
		local bwcheck_opt "bwcheck(`bwcheck')"
	}
	
	if "`bwrestrict'" != ""{
		local bwrestrict_opt "bwrestrict(`bwrestrict')"
	}
	
	if "`weights'" != ""{
		local weights_opt "weights(`weights')"
	}


	****************************************************************************
	** Definition of bias, variances, sample sizes and bandwidths

	if `nodata' == 0 {
	
		if "`bias'" == "" | "`variance'" == ""{
			 qui rdrobust `y' `x' if `touse', c(`c') all `covs_opt' deriv(`deriv') 	 ///
												 p(`p') q(`q') `h_opt' `b_opt' rho(`rho') ///
												 `kernel_opt' `bwselect_opt' `vce_opt' 	 ///
												 scalepar(`scalepar') scaleregul(`scaleregul') ///
												 level(`level') `fuzzy_opt' `covs_drop_opt' ///
												 `masspoints_opt' `bwcheck_opt' `bwrestrict_opt' `stdvars' `weights_opt'
	
			local hl = e(h_l)
			local hr = e(h_r)
			
			if "`bias'" == ""{
				local bias_l = e(bias_l)/(`hl'^(1+`p'-`deriv'))
				local bias_r = e(bias_r)/(`hr'^(1+`p'-`deriv'))
			}
			
			if "`variance'" == ""{			
				mat VL_CL = e(V_cl_l)
				mat VR_CL = e(V_cl_r)
				mat VL_RB = e(V_rb_l)
				mat VR_RB = e(V_rb_r)
				
				if "`clust_opt'" == "cluster" | "`clust_opt'" == "nncluster"{
					qui tab `clustvar' if `x'!=. & `y'!=. & `touse'
					local N = r(r)
				}
				else {
					qui count if `x'!=. & `y'!=. & `touse'
					local N = r(N)
				}
				
				local pos = 1+`deriv'
				local Vl_cl = `N'*(`hl'^(1+2*`deriv'))*VL_CL[`pos',`pos']
				local Vr_cl = `N'*(`hr'^(1+2*`deriv'))*VR_CL[`pos',`pos']
				local Vl_rb = `N'*(`hl'^(1+2*`deriv'))*VL_RB[`pos',`pos']
				local Vr_rb = `N'*(`hr'^(1+2*`deriv'))*VR_RB[`pos',`pos']
			
			}
			
		}
		
		** set default new bandwidth
		
		if "`samph'" == ""{
			local hnew_l = `hl'
			local hnew_r = `hr'
		}
		

		** set default value of tau
		
		if "`tau'" == ""{
			qui sum `y' if `c'-`hnew_l'<=`x' & `x'<`c' & `touse'
			local sd0 = r(sd)
			local tau = 0.5*`sd0'
		}

		
		** Calculate sample sizes
		
		
		if "`clust_opt'"=="cluster" | "`clust_opt'"=="nncluster"{
		
			qui tab `clustvar' if `x'!=. & `y'!=. & `touse'
			local N = r(r)
			
			qui tab `clustvar' if `x'>=`c' & `x'!=. & `y'!=. & `touse'
			local nplus = r(r)
			
			qui tab `clustvar' if `x'<`c' & `x'!=. & `y'!=. & `touse'
			local nminus = r(r)
			
			qui tab `clustvar' if `x'>=`c'&`x'<=`c'+`hnew_r'  & `x'!=. & `y'!=. & `touse'
			local n_hnew_r = r(r)
			
			qui tab `clustvar' if `x'<`c'&`x'>=`c'-`hnew_l'  & `x'!=. & `y'!=. & `touse'
			local n_hnew_l = r(r)	
			
		}
		else {
			qui count if `x'!=. & `y'!=. `ifcond1' `in'
			local N = r(N)
			
			qui count if `x'>=`c' & `x'!=. & `y'!=. & `touse'
			local nplus = r(N)
			
			qui count if `x'<`c' & `x'!=. & `y'!=. & `touse'
			local nminus = r(N)
			
			qui count if `x'>=`c'&`x'<=`c'+`hnew_r'  & `x'!=. & `y'!=. & `touse'
			local n_hnew_r = r(N)
			
			qui count if `x'<`c'&`x'>=`c'-`hnew_l'  & `x'!=. & `y'!=. & `touse'
			local n_hnew_l = r(N)	
		}
		
		
		if "`sampsi'" == ""{
			local ntilde_l = `n_hnew_l'
			local ntilde_r = `n_hnew_r'
		}
		
	}
	
	local ntilde = `nplus'*(`ntilde_r'/`n_hnew_r') + `nminus'*(`ntilde_l'/`n_hnew_l')

	
	****************************************************************************
	** Variance and bias adjustment
	
	** Variance adjustment
	
	local V_rbc = `Vl_rb'/(`ntilde'*(`hnew_l'^(1+2*`deriv'))) + `Vr_rb'/(`ntilde'*(`hnew_r'^(1+2*`deriv')))
	local se_rbc = sqrt(`V_rbc')
	
	if "`all'" != "" {
		local V_conv =  `Vl_cl'/(`ntilde'*(`hnew_l'^(1+2*`deriv'))) + `Vr_cl'/(`ntilde'*(`hnew_r'^(1+2*`deriv')))
		local se_conv = sqrt(`V_conv')
	}
	else {
		local V_conv = `V_rbc'
		local se_conv = `se_rbc'
	}
	

	** Bias adjustment 
			
	local bias = `bias_r'*`hnew_r'^(1+`p'-`deriv') + `bias_l'*`hnew_l'^(1+`p'-`deriv')
	
	
	
	****************************************************************************
	** Power calculation
						
	local power_rbc = 1 - normal((`tau')/`se_rbc'+invnormal(1-`alpha'/2)) ///
							+ normal((`tau')/`se_rbc'-invnormal(1-`alpha'/2))

	local power_conv = 1 - normal((`tau'+`bias')/`se_conv'+invnormal(1-`alpha'/2)) ///
							+ normal((`tau'+`bias')/`se_conv'-invnormal(1-`alpha'/2))
	
	foreach r of numlist 0 2 5 8 {
		local r1 = `r'/10
		local te = `r1'*`tau'
		local power_conv`r' = 1 - normal((`te'+`bias')/`se_conv'+invnormal(1-`alpha'/2)) ///
							+ normal((`te'+`bias')/`se_conv'-invnormal(1-`alpha'/2))
							
		local power_rbc`r' = 1 - normal(`te'/`se_rbc'+invnormal(1-`alpha'/2)) ///
							+ normal(`te'/`se_rbc'-invnormal(1-`alpha'/2))
	}


	
	****************************************************************************
	** Descriptive statistics for display	
		
	if `nodata' == 0 {
	
		* Left panel

		qui count if `x'>=`c' & `x'!=. & `y'!=. & `touse'
		local nplus_disp = r(N)
		
		qui count if `x'<`c' & `x'!=. & `y'!=. & `touse'
		local nminus_disp = r(N)
		
		if "`hl'" == "" | "`hr'" == ""{
			local hl = `hnew_l'
			local hr = `hnew_r'
		}
		
		qui count if `x'>=`c'&`x'<=`c'+`hr'  & `x'!=. & `y'!=. & `touse'
		local n_h_r_disp = r(N)
		
		qui count if `x'<`c'&`x'>=`c'-`hl'  & `x'!=. & `y'!=. & `touse'
		local n_h_l_disp = r(N)
		
		if "`clust_opt'"=="cluster" | "`clust_opt'"=="nncluster"{
			
			qui tab `clustvar' if `x'>=`c' & `x'!=. & `y'!=. & `touse'
			local gplus = r(r)
			
			qui tab `clustvar' if `x'<`c' & `x'!=. & `y'!=. & `touse'
			local gminus = r(r)
			
			qui tab `clustvar' if `x'>=`c'&`x'<=`c'+`hr' & `x'!=. & `y'!=. & `touse'
			local gplus_h_r = r(r)
			
			qui tab `clustvar' if `x'<`c'&`x'>=`c'-`hl' & `x'!=. & `y'!=. & `touse'
			local gminus_h_l = r(r)
		}
		
		if "`hl'" == "" | "`hr'" == ""{
			local hl = .
			local hr = .
		}
		
		* Right panel

		qui count if `x'!=. & `y'!=. `ifcond1' `in'
		local N_disp = r(N)

		if "`bias_cond'" != "" & "`variance'" != ""{
			local bwselect = .
			local kernel_type = .
			local vce_type = .	
		}
		else {
			local bwselect = e(bwselect)
			local kernel_type = e(kernel)
			local vce_type = e(vce_select)
		}
	}
	
	if `nodata' == 1 {
		
		* Left panel
		
		if "`clust_opt'"=="cluster" | "`clust_opt'"=="nncluster"{
			local gplus = `nplus'
			local gminus = `nminus'
		}

		local nplus_disp = .
		local nminus_disp = .
		local n_h_r_disp = .
		local n_h_l_disp = .
		
		local hl = .
		local hr = .
		local p = .
		
		* Right panel

		local N_disp = .

		local bwselect = .
		local kernel_type = .
		local vce_type = .	
		
	}
	
	
	****************************************************************************
	** Display output

		disp ""
		disp as text "{ralign 21: Cutoff c = `c'}"      _col(22) " {c |} " _col(23) in gr "Left of " in yellow "c"  _col(36) in gr "Right of " in yellow "c"  _col(54) as text "Number of obs = "  in yellow %10.0f `N_disp'
		disp as text "{hline 22}{c +}{hline 22}"                                                                                                              _col(54) as text "BW type       = "  in yellow "{ralign 10:`bwselect'}" 
		disp as text "{ralign 21:Number of obs}"        _col(22) " {c |} " _col(23) as result %9.0f `nminus_disp'        _col(37) %9.0f  `nplus_disp'         _col(54) as text "Kernel        = "  in yellow "{ralign 10:`kernel_type'}" 
		disp as text "{ralign 21:Eff. Number of obs}"   _col(22) " {c |} " _col(23) as result %9.0f `n_h_l_disp'      	 _col(37) %9.0f  `n_h_r_disp'         _col(54) as text "VCE method    = "  in yellow "{ralign 10:`vce_type'}" 
		disp as text "{ralign 21:BW loc. poly. (h)}"	_col(22) " {c |} " _col(23) as result %9.3f `hl'     	    	 _col(37) %9.3f  `hr'				  _col(54) as text "Derivative    = "  in yellow %10.0f `deriv'
		disp as text "{ralign 21:Order loc. poly. (p)}"	_col(22) " {c |} " _col(23) as result %9.0f `p'     	    	 _col(37) %9.0f  `p'				  _col(54) as text "HA:       tau = "  in yellow %10.3f `tau'
		if "`clust_opt'" == "cluster" | "`clust_opt'" == "nncluster"{			
			if "`all'" != ""{
				disp as text "{ralign 21:Number of clusters}"        _col(22) " {c |} " _col(23) as result %9.0f `gminus'        _col(37) %9.0f  `gplus'      _col(54) as text "Size dist     = "  in yellow %10.4f `power_conv0'-`alpha'
				disp as text "{ralign 21:Eff. Num. of clusters}"   _col(22) " {c |} " _col(23) as result %9.0f `gminus_h_l'      	 _col(37) %9.0f  `gplus_h_r'				
			}
			else{
				disp as text "{ralign 21:Number of clusters}"        _col(22) " {c |} " _col(23) as result %9.0f `gminus'        _col(37) %9.0f  `gplus'
				disp as text "{ralign 21:Eff. Num. of clusters}"   _col(22) " {c |} " _col(23) as result %9.0f `gminus_h_l'      _col(37) %9.0f  `gplus_h_r'
			}
			disp as text "{hline 22}{c +}{hline 22}"
		}
		else{
			if "`all'" != ""{
			disp as text "{hline 22}{c +}{hline 22}" 																											  _col(54) as text "Size dist     = "  in yellow %10.4f `power_conv0'-`alpha'
			}
			else {
			disp as text "{hline 22}{c +}{hline 22}"
			}	
		}
		
		disp as text "{ralign 21:Sampling BW}"		    _col(22) " {c |} " _col(23) as result %9.3f `hnew_l'    	_col(37) %9.3f  `hnew_r'				  	  
		
		
		if "`clust_opt'"=="cluster" | "`clust_opt'"=="nncluster" {
			disp as text "{ralign 21:New cluster sample}" _col(22) " {c |} " _col(23) as result %9.0f `ntilde_l'  	_col(37) %9.0f  `ntilde_r'
		}
		else{
			disp as text "{ralign 21:New sample}"			_col(22) " {c |} " _col(23) as result %9.0f `ntilde_l'  	_col(37) %9.0f  `ntilde_r'
		}
		disp ""

		if `nodata' == 0 {
			if "`covs'" == ""{
				di as text _newline "Outcome: " as res "`y'" as text ". Running variable: " as res "`x'" as text "."
			}
			else {
				di as text _newline "Outcome: " as res "`y'" as text ". Running variable: " as res "`x'" as text ". Number of covariates: " as res "`ncovs'" as text"."
			}
		}
		
		di as text "{hline 22}{c TT}{hline 56}"
		di as text "Power against:" _col(22) " {c |}"	 				   _col(25) as text "H0: tau= "  			_col(37) "0.2*tau = " 		 _col(49) "0.5*tau = " 			_col(61) "0.8*tau = " 		_col(75) "tau ="
		di 							_col(22) " {c |}"	 				   _col(26) as result %7.3f 0 				_col(39) %7.3f 0.2*`tau' 	 _col(51) %7.3f 0.5*`tau' 		_col(63) %7.3f 0.8*`tau' 	_col(73) %7.3f `tau'

		di as text "{hline 22}{c +}{hline 56}"
		di as text "{ralign 21:Robust bias-corrected}"	_col(22) " {c |} " _col(28) as result  %5.3f `power_rbc0'   _col(41) %5.3f `power_rbc2'  _col(53) %5.3f `power_rbc5'    _col(65) %5.3f `power_rbc8'  _col(75) %5.3f `power_rbc'
		if "`all'" !="" {
			di as text "{ralign 21:Conventional}"		_col(22) " {c |} " _col(28) as result  %5.3f `power_conv0'  _col(41) %5.3f `power_conv2' _col(53) %5.3f `power_conv5'   _col(65) %5.3f `power_conv8' _col(75) %5.3f `power_conv'
		}
		di as text "{hline 22}{c BT}{hline 56}"
		
		if "`clust_opt'"=="cluster" | "`clust_opt'"=="nncluster" {
			disp as text "Standard errors clustered by " as res "`clustvar'" as text "."
		}
		
		
	****************************************************************************
	** Power function plot

	if "`plot'" != "" {
		if "`graph_range'" != ""{
			tokenize `graph_range'
			local left `1'
			local right `2'
		}
		else {
			local left = -1.5*`tau'
			local right = 1.5*`tau'
			local left = round(`left',.1)
			local right = round(`right',.1)
		}
		if "`graph_step'" != ""{
			local step `graph_step'
		}
		else {
			local step = (`right'-`left')/5
		}
		if "`graph_options'" == "" {
		
			if "`all'" != ""{
				twoway (function y = 1 - normal(x/`se_rbc'+invnormal(1-`alpha'/2)) ///
									 + normal(x/`se_rbc'-invnormal(1-`alpha'/2)), ///
							range(`left' `right')) ///				   
						(function y = 1 - normal((x+`bias')/`se_conv'+invnormal(1-`alpha'/2)) ///
									 + normal((x+`bias')/`se_conv'-invnormal(1-`alpha'/2)), ///
							range(`left' `right')), ///
				   xline(`tau', lpattern(shortdash) lwidth(thin)) ///
				   xline(0, lpattern(solid) lwidth(thin) lcolor(gray)) ///
				   yline(`alpha', lpattern(shortdash) lcolor(black) lwidth(thin)) ///
				   yline(`power_rbc', lcolor(eltgreen) lpattern(shortdash) lwidth(vthin)) ///
				   legend(label(1 "robust bias corrected") label(2 "conventional"))	///
				   ytitle("power") xtitle("tau") xlabel(`left'(`step')`right') ///
				   note("Power function for N_l = `n_hnew_l', N_r = `n_hnew_r', alpha = `alpha' (horizontal black dashed line).")
			}
			else {
				twoway (function y = 1 - normal(x/`se_rbc'+invnormal(1-`alpha'/2)) ///
									 + normal(x/`se_rbc'-invnormal(1-`alpha'/2)), ///
							range(`left' `right')), ///
				   xline(`tau', lpattern(shortdash) lwidth(thin)) ///
				   xline(0, lpattern(solid) lwidth(thin) lcolor(gray)) ///
				   yline(`alpha', lpattern(shortdash) lcolor(black) lwidth(thin)) ///
				   yline(`power_rbc', lcolor(eltgreen) lpattern(shortdash) lwidth(vthin)) ///
				   legend(label(1 "robust bias corrected"))	///
				   ytitle("power") xtitle("tau") xlabel(`left'(`step')`right') ///
				   note("Power function for N_l = `n_hnew_l', N_r = `n_hnew_r', alpha = `alpha' (horizontal black dashed line).")
			}
		}
		else {
			if "`all'" != "" {
				twoway (function y = 1 - normal(x/`se_rbc'+invnormal(1-`alpha'/2)) ///
									 + normal(x/`se_rbc'-invnormal(1-`alpha'/2)), ///
							range(`left' `right')) ///					   
						(function y = 1 - normal((x+`bias')/`se_conv'+invnormal(1-`alpha'/2)) ///
									 + normal((x+`bias')/`se_conv'-invnormal(1-`alpha'/2)), ///
							range(`left' `right')), ///
				    legend(label(1 "robust bias corrected") label(2 "conventional"))	///
					xlabel(`left'(`step')`right') `graph_options'
			}
			else {
				twoway (function y = 1 - normal(x/`se_rbc'+invnormal(1-`alpha'/2)) ///
									 + normal(x/`se_rbc'-invnormal(1-`alpha'/2)), ///
							range(`left' `right')), ///
				    legend(label(1 "robust bias corrected"))	///
					xlabel(`left'(`step')`right') `graph_options'
			}
		}
	}
	

	****************************************************************************
	** Return values

	if "`all'" != ""{
		return scalar power_conv = `power_conv'
		return scalar se_conv = `se_conv'
	}
	return scalar bias_r = `bias_r'
	return scalar bias_l = `bias_l'
	return scalar Vr_rb = `Vr_rb'
	return scalar Vl_rb = `Vl_rb'
	return scalar power_rbc = `power_rbc'
	return scalar se_rbc = `se_rbc'
	return scalar sampsi_r = `ntilde_r'
	return scalar sampsi_l = `ntilde_l'
	return scalar samph_r = `hnew_r'
	return scalar samph_l = `hnew_l'
	return scalar N_r = `nplus'
	return scalar N_l = `nminus'
	return scalar N_h_r = `n_hnew_r'
	return scalar N_h_l = `n_hnew_l'
	return scalar tau = `tau'
	return scalar alpha = `alpha'

end
